Name
Abstract | ||
|---|---|---|
The Dragon Promoter Finder is an advanced system for promoter recognition in vertebrates. It uses a collection of models based on multisensor integration, signal processing, and artificial neural networks. The system uses newly developed sensors based on the statistical concept of oligonucleotide positional distributions in specific functional regions of DNA. These distributions are modeled as a set of position weight matrices of the most significant oligonucleotides. The authors calibrated the system to minimize the number of false-positive predictions for various prespecified sensitivity levels. When evaluated on a large and diverse human sequence set, it exhibited several times higher accuracy than several other publicly available general promoter recognition systems. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/MIS.2002.1024754 | Intelligent Systems, IEEE |
Keywords | Field | DocType |
DNA,artificial intelligence,biology computing,genetics,neural nets,pattern recognition,sensitivity,sensor fusion,signal processing,zoology,DNA region,Dragon Promoter Finder,accuracy,artificial neural networks,biological gene activation,false-positive prediction minimization,gene transcription start site,intelligent system,multi-sensor integration,sensitivity levels,signal processing,vertebrate promoter recognition | Data mining,Biological activation,Gene,Transcription (biology),Computer science,Gene prediction,DNA,Vertebrate,Artificial intelligence,Computational biology,Artificial neural network | Journal |
Volume | Issue | ISSN |
17 | 4 | 1541-1672 |
Citations | PageRank | References |
18 | 3.51 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vladimir B. Bajic | 1 | 18 | 3.85 |
| Allen Chong | 2 | 65 | 7.96 |
| S H Seah | 3 | 79 | 10.51 |
| Vladimir Brusic | 4 | 551 | 63.37 |